林地变化驱动力研究旨在揭示林地变化背后的驱动因素及其作用机制,是动态模拟、预测林地利用变化的前提工作。逻辑回归模型是研究林地变化驱动力的常见方法,但目前还没有学者对此进行系统的梳理。文中对逻辑回归模型在国内外林地变化驱动力研究中的应用进行综述,并提出对未来相关研究的建议;通过文献分析法、归纳法等研究发现,相较于其他方法逻辑回归模型具有适用于因变量是分类变量的案例、重视空间机制等优势;提出未来通过逻辑回归模型进行林地变化驱动力研究需要考虑数据的空间自相关性,选用恰当的研究单元、尺度以及变量。 The study on the driving force of forestland change aims at revealing the driving forces behind the change of forestland and its mechanism of action, which is a prerequisite for dynamic simulation and forestry land use change prediction. Logistic regression model is a common method to study the driving force of forestland change, but no one has systematically sorted it. In this paper, the application of logistic regression model in the study of the driving force of forestland change at home and abroad is reviewed, and some suggestions for future research are proposed. Through literature analysis, induction and other studies, it is found that compared with other methods, It is necessary to consider the spatial autocorrelation of data and propose the appropriate research units, scales and variables for future research on the driving force of forestland change through logistic regression model.